STATISTICS
Standard Deviation
Article by:Geoffrey Hunter
Date Published: | |
Last Modified: |
Contents
This page is a work-in-progress.
Overview
The standard deviation is a metric which is used to measure the amount of variation in a set of data values.
The standard deviation has the same units as the data.
Equation
$$ \sigma = \sqrt{\frac{ \sum{(x - \bar{x})?^2}}{n}} $$
where:
\( \bar{x} \) is the mean (average) of the samples
\( n \) is the number of samples
For example,
4, 8, 7, 3, 12
\begin{align}
\bar{x} &= \frac{1}{5} * (4+8+7+3+12)\\
&= 6.8\\
\\
\sum{(x - \bar{x})} = (4-6.8)^2+(8-6.8)^2+(7-6.8)^2+(3-6.8)^2+(12-6.8)^2\\
=
\end{align}
Software
You can calculated the standard deviation of an array in Numpy with np.std()
:
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By default, the array is flattened. However, you can specify an axis
on which to calculate the standard deviation.
Authors

This work is licensed under a Creative Commons Attribution 4.0 International License .
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